Senior Data Scientist - Multi‑Omics AI & Target Identification

Pierre Fabre Laboratories; Toulouse; Hybride; EUR 70 000 - 110 000; Plein temps

Avantages offerts par ce poste

Profit-sharing

Shareholding with matching

Health insurance

Provident insurance

RTT & holidays 16 days + 25 personal

Public transport subsidies

Résumé du poste

Pierre Fabre Laboratories in Toulouse seeks a Senior Data Scientist to lead multi-omics AI initiatives for target identification and precision medicine. You will design AI systems learning from genomics, transcriptomics, and other omics data to uncover cancer vulnerabilities and translate discoveries into drug development.

The role collaborates with biologists and translational scientists, leveraging HPC/cloud environments and a strong emphasis on robust, interpretable AI frameworks across R&D.

Qualifications

• PhD or Master’s in Data Science, Computational Biology, or related field.
• 5+ years of data science experience in life sciences.
• Demonstrated multi-omics data analysis for target discovery/translational research.
• Hands-on experience building ML and DL models.

Responsabilités

• Develop ML/DL models to integrate multi-omics data for target prioritization.
• Identify molecular mechanisms and pathways across cancer indications.
• Support target discovery, toxicity prediction, and patient stratification.
• Design models using representation learning, self-supervised learning, and domain adaptation.
• Apply transformer-based architectures to biological/omics data.
• Ensure model robustness, reproducibility, and interpretability.

Connaissances

PhD or Master’s in Data Science/Comput

5+ years experience

Multi-omics analysis

Hands-on ML/DL

Formation

PhD in Data Science

Master’s in Computational Biology

Outils

Python

PyTorch

Transformers

HPC/Cloud

Description du poste

Your role within a pioneering company in full expansion:

We are seeking in Toulouse (Oncopole- Langlade Location) a talented and highly motivated Senior Data Scientist - Multi‑Omics AI & Target Identification with strong expertise in multi‑omics analysis, machine learning, and AI for biological data to accelerate target identification, translational research, and precision medicine strategies.

As a key member of the Data Science & Biometry Department within Pierre Fabre R&D Medical Care, you will design and develop AI systems capable of learning from high‑dimensional biological data (genomics, transcriptomics, proteomics, functional screens) to deepen disease understanding, uncover pathway‑level mechanisms, and reveal cancer vulnerabilities across indications.

This role sits at the interface of AI research, computational biology, and drug discovery, and is embedded within the Methods & Innovation team, responsible for cross‑functional initiatives involving advanced AI methodologies.

Key Responsibilities:

• Develop and apply machine learning and deep learning models to integrate multi‑omics data for target identification and prioritization.
• Contribute to biological and disease understanding by identifying molecular mechanisms, pathways, and vulnerabilities across cancer indications.
• Support diverse downstream assessments, including target discovery, toxicity prediction, and patient stratification.
• Design and train advanced models leveraging representation learning, self‑supervised learning, and domain adaptation.
• Apply and adapt transformer‑based architectures to biological and omics data.
• Ensure strong standards for model robustness, reproducibility, interpretability, and scientific validity.
• Work with HPC and/or cloud environments to scale model training and experimentation.
• Collaborate closely with biologists, translational scientists, and drug discovery teams to translate biological questions and hypotheses into AI‑driven solutions.
• Contribute to shared AI frameworks and reusable methodological components across R&D.

This position is based in Toulouse with flexibility for remote work.

We offer an attractive remuneration/benefits package: Incentives, profit-sharing, Pierre Fabre shareholding with matching contribution, health and provident insurance, 16 days of holidays (RTT) in addition to 25 days of personal holidays, public transport participation.

Your skills at the service of innovative projects:

• PhD or Master’s degree in Data Science, Computational Biology, or a related field.
• 5+ years of experience in data science applied to life sciences.
• Demonstrated experience in multi‑omics data analysis for target discovery or translational research.
• Hands‑on experience developing machine learning and deep learning models.

Technical Skills:

• Strong proficiency in Python.
• Experience with deep learning frameworks (e.g., PyTorch).
• Solid knowledge of modern ML approaches, including transformers, representation learning, self‑supervised learning, and domain adaptation.
• Familiarity with HPC and/or cloud computing environments.
• Strong grounding in bioinformatics, cancer biology, and pathway-level reasoning.

Soft Skills & Mindset

• Strong analytical and structured thinking.
• Ability to translate biological, scientific, and strategic challenges into effective AI solutions.
• High intellectual curiosity and innovation mindset.

Professional proficiency in English (written and oral).